Frequency and burden of potentially treatable symptoms in glioma patients with stable disease.

Background & aims: Glioma patients experience a multitude of symptoms that negatively affect their health-related quality of life. Symptoms vary greatly across disease phases, and the patients' stable phase might be particularly suitable for assessing and treating symptoms. Identifying symptoms and patients' needs is a first step toward improving patient care. In glioma patients with stable disease, we assessed the frequency and burden of patient-reported symptoms, examined how these symptoms co-occur, and also determined whether patients would consider treatment to ameliorate specific symptoms. Methods: In this retrospective study, patients rated the frequency and burden of seventeen symptoms on a seven-point Likert scale and stated whether they would consider treatment for these symptoms. Correlations between frequency, burden, and considering treatment were evaluated with Kendall's Tau correlation coefficients. Based on partial correlations between symptom frequencies we visualized the symptoms as a network. Results: Fifty-two glioma patients with stable disease were included (31 WHO grade II/III, 21 WHO grade IV). The top five symptoms were fatigue, memory problems, reduced physical fitness, concentration problems, and drowsiness. Fatigue had the highest median frequency (4.5, interquartile range 2.5). Over half of the patients experienced three or more symptoms simultaneously and associations between all symptoms were depicted as a network. Overall, 35% of patients would consider treatment for at least one symptom. The wish to undergo symptom treatment correlated only moderately with symptom frequency and burden (range of correlations 0.24-0.57 and 0.28-0.61, respectively). Conclusion: Glioma patients with stable disease experience multiple symptoms with a consequently high symptom burden. Despite the high prevalence of symptoms, the inclination for symptom management interventions was relatively low. The most frequent and burdensome symptoms and the way they are interrelated could serve as a roadmap for future research on symptom management in these patients.

Cannabinoids to Improve Health-Related Quality of Life in Patients with Neurological or Oncological Disease: A Meta-Analysis.

Background: Cannabinoids have been suggested to alleviate frequently experienced symptoms of reduced mental well-being such as anxiety and depression. Mental well-being is an important subdomain of health-related quality of life (HRQoL). Reducing symptoms and maintaining HRQoL are particularly important in malignant primary brain tumor patients, as treatment options are often noncurative and prognosis remains poor. These patients frequently report unprescribed cannabinoid use, presumably for symptom relieve. As studies on brain tumor patients specifically are lacking, we performed a meta-analysis of the current evidence on cannabinoid efficacy on HRQoL and mental well-being in oncological and neurological patients. Methods: We performed a systematic PubMed, PsychINFO, Embase, and Web of Science search according to PRISMA guidelines on August 2 and 3, 2021. We included randomized controlled trials (RCTs) that assessed the effects of tetrahydrocannabinol (THC) or cannabidiol (CBD) on general HRQoL and mental well-being. Pooled effect sizes were calculated using Hedges g. Risk of bias of included studies was assessed using Cochrane's Risk of Bias tool. Results: We included 17 studies: 4 in oncology and 13 in central nervous system (CNS) disease. Meta-analysis showed no effect of cannabinoids on general HRQoL (g=-0.02 confidence interval [95% CI -0.11 to 0.06]; p=0.57) or mental well-being (g=-0.02 [95% CI -0.16 to 0.13]; p=0.81). Conclusions: RCTs in patients with cancer or CNS disease showed no effect of cannabinoids on HRQoL or mental well-being. However, studies were clinically heterogeneous and since many glioma patients currently frequently use cannabinoids, future studies are necessary to evaluate its value in this specific population.

Toward unraveling the correlates of fatigue in glioma.

Background: Even though fatigue is one of the most prevalent and burdensome symptoms in patients with glioma, its etiology and determinants are still poorly understood. We aimed to identify which demographic, tumor- and treatment-related characteristics and patient-reported outcome measures (PROMs) are associated with or are predictors of fatigue in glioma. Methods: In this retrospective observational study, we included glioma patients with preoperative and postoperative assessments including PROMs on fatigue, depression, cognitive functioning, and health-related quality of life (HRQoL). Linear mixed models were used to identify which clinical factors and PROMs were associated with fatigue and linear multiple regression was used to detect predictors of postoperative fatigue. Results: In this study, 222 patients were included (78% grade II-III glioma, 22% grade IV). These patients had performed 333 assessments (193 preoperative and 116 one year postoperatively). Of all assessments, 39% was indicative of severe fatigue. Several HRQoL domains, depression, and right-sided tumors were significantly associated with fatigue (marginal R 2 = 0.63). Contrary to common expectations, tumor type, treatment-related factors, and timing of the assessment, were not associated with fatigue. In a subgroup of 70 patients with follow-up assessments, preoperative fatigue, and physical functioning were predictors of postoperative fatigue (adjusted R 2 = 0.31). Conclusion: Fatigue is a complex symptom, which should not solely be attributed to the tumor or its treatment, but is instead related to different aspects of mood and HRQoL. These insights are important in understanding fatigue and could guide symptom management, especially in patients with lower-grade tumors.

Postoperative oscillatory brain activity as an add-on prognostic marker in diffuse glioma.

INTRODUCTION: Progression-free survival (PFS) in glioma patients varies widely, even when stratifying for known predictors (i.e. age, molecular tumor subtype, presence of epilepsy, tumor grade and Karnofsky performance status). Neuronal activity has been shown to accelerate tumor growth in an animal model, suggesting that brain activity may be valuable as a PFS predictor. We investigated whether postoperative oscillatory brain activity, assessed by resting-state magnetoencephalography is of additional value when predicting PFS in glioma patients. METHODS: We included 27 patients with grade II-IV gliomas. Each patient's oscillatory brain activity was estimated by calculating broadband power (0.5-48 Hz) in 56 epochs of 3.27 s and averaged over 78 cortical regions of the Automated Anatomical Labeling atlas. Cox proportional hazard analysis was performed to test the predictive value of broadband power towards PFS, adjusting for known predictors by backward elimination. RESULTS: Higher broadband power predicted shorter PFS after adjusting for known prognostic factors (n = 27; HR 2.56 (95% confidence interval (CI) 1.15-5.70); p = 0.022). Post-hoc univariate analysis showed that higher broadband power also predicted shorter overall survival (OS; n = 38; HR 1.88 (95% CI 1.00-3.54); p = 0.038). CONCLUSIONS: Our findings suggest that postoperative broadband power is of additional value in predicting PFS beyond already known predictors.